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Is The Applied AI In Agriculture Market Expanding? Latest Size Estimates And 2030 Projections
The applied ai in agriculture market size has experienced substantial growth in recent years. It is anticipated to increase from $3.75 billion in 2025 to $4.86 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 29.6%. Historically, this expansion has been driven by the early implementation of basic automation in farming, an increasing requirement for efficient crop monitoring, the rising volume of agricultural data generated by sensors, the need to lessen dependence on manual labor, and the advent of precision farming methodologies.
The applied AI in agriculture market is projected to experience substantial growth in the coming years. It is anticipated to reach $13.57 billion in 2030, demonstrating a compound annual growth rate (CAGR) of 29.3%. This expansion during the forecast period is driven by the increasing application of AI-enabled predictive analytics, the growing deployment of autonomous agricultural machinery, rising investment in digital farm platforms, the expansion of AI-driven livestock monitoring, and the demand for sustainable farming supported by AI solutions. Key trends expected in the forecast period include the increasing adoption of AI-based crop and soil health assessments, the broadening of data-driven farm decision-making practices, the rising integration of automation in large-scale farming operations, a growing demand for real-time agricultural monitoring solutions, and an enhanced focus on AI-supported yield enhancement techniques.
Free Applied AI In Agriculture Market Sample: Market Size, Growth Drivers And Competitive Landscape:
Applied AI In Agriculture Market Drivers Explained: What Is Supporting A 29.3% CAGR?
The increasing crop productivity is anticipated to propel the growth of the applied AI in agriculture market going forward. Crop productivity defines the measure of crop output, commonly expressed as yield per unit area of land. This increase in crop productivity is due to advancements in agricultural technology and practices, including improved crop varieties, efficient irrigation methods, and the use of precision farming techniques. Applied AI in agriculture enhances crop productivity by optimizing farming practices through data-driven insights, predictive analytics, and automation. As an illustration, in January 2024, the United States Department of Agriculture, a US-based federal executive department responsible for developing and executing federal laws, reported that the average yield for all United States rice was estimated at 7,649 pounds per acre in 2023, marking an increase of 264 pounds from the 2022 average yield of 7,385 pounds per acre. Consequently, increasing crop productivity is driving the applied AI in agriculture market.
Applied AI In Agriculture Market Segment Guide: Main Divisions And Subsegments
The applied ai in agriculture market covered in this report is segmented –
1) By Component: Hardware, Software, Service
2) By Technology: Machine Learning And Deep Learning, Predictive Analytics, Computer Vision
3) By Application: Precision Farming, Drone Analytics, Agriculture Robots, Livestock Monitoring, Other Applications
Subsegments:
1) By Hardware: Sensors (Soil, Climate, Crop Monitoring), Drones For Crop Surveillance, Automated Tractors And Harvesters, GPS & GIS Systems For Precision Farming, Imaging Systems, IoT Devices For Agricultural Monitoring, Robotics For Seeding, Planting, And Weeding
2) By Software: Farm Management Software, AI-Based Crop Prediction Software, Precision Agriculture Software, Irrigation Management Software, Pest And Disease Detection Software, Data Analytics And Visualization Tools, Supply Chain Optimization Software, Machine Learning Algorithms For Yield Prediction
3) By Service: AI Integration And Implementation Services, Data Analytics Services For Crop And Soil Analysis, Cloud-Based Agricultural Services, AI Model Training And Customization Services, Maintenance And Support Services, Consultation And Advisory Services For AI Adoption In Agriculture
Applied AI In Agriculture Market Trends And Opportunities For 2026–2030
Major companies operating in the applied AI in agriculture market are increasingly concentrating on developing innovative solutions, such as AI-based tools, to preserve their market position. AI-based tools are defined as software and technologies that employ artificial intelligence to improve various elements of farming and agricultural methods. For example, in July 2024, Google LLC, a US-based technology company, unveiled an innovative AI-based tool called Agricultural Landscape Understanding (ALU) to enhance agricultural practices in India, specifically targeting drought preparedness and irrigation management. This tool utilizes high-resolution satellite imagery and machine learning to deliver customized insights for individual farm fields, addressing the varied requirements of India’s agricultural landscape. By establishing clear field boundaries, the ALU tool can analyze different factors like crop type, field size, and proximity to water sources, which are essential for effective irrigation and drought management strategies. The primary aim of this initiative is to empower farmers by boosting crop yields, easing access to capital, and improving market access for agricultural products.
Which Major Players Are Active In The Applied AI In Agriculture Market?
Major companies operating in the applied ai in agriculture market are Microsoft Corporation, BASF SE, International Business Machines Corporation, Bayer AG, Deere & Company, SAP SE, CNH Industrial N.V., Kubota Corporation, Corteva Inc., AGCO Corporation, Trimble Inc., Raven Industries Inc., The Climate Corporation, AG Leader Technology, The BAE Systems Taranis, Farmers Edge Inc., PrecisionHawk, AgEagle Aerial Systems, Descartes Labs Inc., Prospera Technologies Ltd., Agribotix, Gamaya
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Applied AI In Agriculture Market World Regions Compared: Which Leads In Revenue?
North America was the largest region in the applied AI in agriculture market in 2025. The regions covered in the applied ai in agriculture market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
